code: def to_json(self):
      if len(self.columns) == 0:
          return None
      data_json = {
          "scale": list(self.scale.scale_),
          "mean": list(self.scale.mean_),
          "var": list(self.scale.var_),
          "n_samples_seen": int(self.scale.n_samples_seen_),
          "n_features_in": int(self.scale.n_features_in_),
          "columns": self.columns,
          "scale_method": self.scale_method,
      }
      if self.X_min_values is not None:
          data_json["X_min_values"] = list(self.X_min_values)
      return data_json
  
file_path: mljar-supervised/supervised/preprocessing/scale.py
imports: import numpy
  import pandas
  from sklearn import preprocessing
label_desc: Use image node_id 5 for calling the Scale obj's underlying member method code with example usage: obj.to_json() and returns: data_json, None